Radiographic image processing apparatus, scattered radiation correction method, and computer readable storage medium

ABSTRACT

A radiographic image processing apparatus includes a hardware processor, which determines the intensity of an edge in a radiographic image obtained by radiographically imaging a subject, sets a weighting factor to be used in extracting a frequency component from the radiographic image according to a determination result of the edge intensity, extracts the frequency component from the radiographic image using the weighting factor having been set, multiplies the extracted frequency component by a scattered radiation content rate to estimate a scattered radiation component in the radiographic image, multiplies the estimated scattered radiation component by a scattered radiation removal rate to generate a scattered radiation image representing the scattered radiation component to be removed from the radiographic image, and performs scattered radiation correction on the radiographic image by subtracting the scattered radiation image from the radiographic image.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims priority under 35 U.S.C. § 119 toJapanese Patent Application No. 2018-009644, filed on Jan. 24, 2018, theentirety of which is hereby incorporated by reference herein and forms apart of the specification.

BACKGROUND 1. Technical Field

The present invention relates to a radiographic image processingapparatus, a scattered radiation correction method, and a computerreadable storage medium.

2. Description of the Related Art

Capturing a radiographic image of a subject with radiation transmittedthrough the subject raises a problem that the radiation scatters in thesubject according to the thickness of the subject and generatedscattered radiation deteriorates the contrast of the acquiredradiographic image. Therefore, at the time of capturing a radiographicimage, a scattered radiation removal grid (hereinafter, simply referredto as “grid”) can be provided between the subject and a radiationdetector so that the radiation detector is not irradiated with scatteredradiation when detecting radiation and acquiring the radiographic image.Using the grid to perform imaging can improve the contrast of theradiographic image because the radiation detector is less likely to beirradiated with radiations scattered by the subject. However, using thegrid raises a problem that the workload of grid arrangement at the timeof portable imaging to be performed in a hospital room or the like islarge and the burden on a patient is heavy and further the grid may cutthe radiations traveling straight when the applied direction of theradiations is inappropriate. Therefore, in order to improve the contrastlowered by the scattered radiation components of the radiations, it isconventionally known to perform image processing on the radiographicimage for correction of the scattered radiation.

For example, Patent Literature 1 (JA2015-100543A) discloses a techniquecapable of generating a band image that represents a frequency componentfor each of a plurality of frequency bands by frequency decomposing anoriginal image, converting the band image based on irradiation fieldinformation, subject information, imaging conditions and the like andgenerating a converted band image by multiplying a weight determined foreach frequency band, generating a scattered radiation image by combininga plurality of converted band images having been generated, andsubtracting the scattered radiation image from the original image togenerate a radiographic image from which the scattered radiation hasbeen removed. In general, it is known that the amount of containedscattered radiation is relatively large in a low-frequency band and issmaller in a high-frequency band. Therefore, in Patent Literature 1, theweight is determined so that the weight increases as the frequency bandbecomes lower.

Further, Patent Literature 2 (JP09-270004A) discloses a techniquecapable of generating a low-frequency component image by processing anoriginal image with a lowpass filter, adjusting the generatedlow-frequency component image according to scattered radiation influencedegree by the edge, and subtracting the adjusted low-frequency componentimage from the original image to generate a radiographic image fromwhich the scattered radiation has been removed.

The techniques discussed in Patent Literatures 1 and 2 are techniquesbased on the recognition that the amount of contained scatteredradiation is relatively large in the low-frequency band. However,experiments conducted by inventors of the present invention haverevealed that the scattered radiation contains a certain amount ofhigh-frequency components, the amount of frequency components in thehigh-frequency band increases in the vicinity of strong edges and theamount of frequency components in the low-frequency band increases inthe vicinity of weak edges. Therefore, according to the techniquediscussed in Patent Literature 1 or Patent Literature 2, estimationerrors of high-frequency components of the scattered radiation increase,especially, in the vicinity of strong edges, and high-frequencycomponents are more likely to be emphasized after removal of thescattered radiation. Therefore, removal of scattered radiation in thevicinity of edges cannot be precisely performed.

SUMMARY

The present invention intends to obtain a radiographic image from whichscattered radiation has been precisely removed by improving the accuracyin estimating scattered radiation in the vicinity of edges in theradiographic image, thereby.

To achieve at least one of the above-mentioned objects, a radiographicimage processing apparatus according to one aspect of the presentinvention includes a hardware processor that determines the intensity ofan edge in a radiographic image obtained by radiographically imaging asubject, sets a weighting factor to be used in extracting a frequencycomponent from the radiographic image according to a determinationresult of the edge intensity, extracts the frequency component from theradiographic image using the weighting factor having been set,multiplies the extracted frequency component by a scattered radiationcontent rate to estimate a scattered radiation component in theradiographic image, multiplies the estimated scattered radiationcomponent by a scattered radiation removal rate to generate a scatteredradiation image representing the scattered radiation component to beremoved from the radiographic image, and performs scattered radiationcorrection on the radiographic image by subtracting the scatteredradiation image from the radiographic image.

Further, a scattered radiation correction method according to one aspectof the present invention is a scattered radiation correction method fora radiographic image processing apparatus that performs scatteredradiation correction on a radiographic image obtained byradiographically imaging a subject, the method including:

determining the intensity of an edge in the radiographic image,

setting a weighting factor to be used in extracting a frequencycomponent from the radiographic image according to a determinationresult of the edge intensity,

extracting the frequency component from the radiographic image using theweighting factor having been set,

multiplying the extracted frequency component by a scattered radiationcontent rate to estimate a scattered radiation component in theradiographic image,

multiplying the estimated scattered radiation component by a scatteredradiation removal rate to generate a scattered radiation imagerepresenting the scattered radiation component to be removed from theradiographic image, and

performing scattered radiation correction on the radiographic image bysubtracting the scattered radiation image from the radiographic image.

Further, a computer readable storage medium according to one aspect ofthe present invention is a non-transitory computer readable storagemedium storing a program that causes a computer, to be used for aradiographic image processing apparatus that performs scatteredradiation correction on a radiographic image obtained byradiographically imaging a subject, to determine the intensity of anedge in the radiographic image obtained by radiographically imaging thesubject, set a weighting factor to be used in extracting a frequencycomponent from the radiographic image according to a determinationresult of the edge intensity, extract the frequency component from theradiographic image using the weighting factor having been set, multiplythe extracted frequency component by a scattered radiation content rateto estimate a scattered radiation component in the radiographic image,multiply the estimated scattered radiation component by a scatteredradiation removal rate to generate a scattered radiation imagerepresenting the scattered radiation component to be removed from theradiographic image, and perform scattered radiation correction on theradiographic image by subtracting the scattered radiation image from theradiographic image.

BRIEF DESCRIPTION OF THE DRAWINGS

The above objects, advantageous effects and features of the presentinvention will be more fully understood from the following detaileddescription and the accompanying drawing. However, these are notintended to limit the present invention.

FIG. 1 is a view illustrating the entire configuration of a radiographicimaging system according to an exemplary embodiment of the presentinvention.

FIG. 2 is a block diagram illustrating a functional configuration of aconsole illustrated in FIG. 1.

FIG. 3 is a view schematically illustrating an exemplary flow ofscattered radiation correction processing A, which can be executed by acontroller illustrated in FIG. 2 according to a first exemplaryembodiment.

FIG. 4 is a view illustrating filter processing.

FIG. 5 is a view illustrating a relationship between a weighting factorand a pixel value difference according to the first exemplaryembodiment.

FIG. 6A is a view illustrating a result of scattered radiation removalbased on a frequency component image obtained by performing filterprocessing using a constant weighting factor.

FIG. 6B is a view illustrating a result of scattered radiation removalbased on a frequency component image obtained by performing filterprocessing using a weighting factor reflecting the edge.

FIG. 7 is a view schematically illustrating an exemplary flow ofscattered radiation correction processing B that can be executed by thecontroller illustrated in FIG. 2 according to a second exemplaryembodiment.

FIG. 8 is a view illustrating exemplary non-local means filterprocessing.

FIG. 9 is a view schematically illustrating an exemplary flow ofscattered radiation correction processing C that can be executed by thecontroller illustrated in FIG. 2 according to a third exemplaryembodiment.

FIG. 10 is a view illustrating frequency decomposition using only onekernel.

FIG. 11 is a view illustrating frequency decomposition using a pluralityof kernels that are mutually different in size and/or shape.

FIG. 12A is a view illustrating an exemplary relationship between thedistance from an attentional pixel and the weighting factor in a kernelto be used in the frequency decomposition and differentiated in shape.

FIG. 12B is a view illustrating an exemplary relationship between thedistance from an attentional pixel and the weighting factor in anotherkernel to be used in the frequency decomposition and differentiated inshape.

FIG. 12C is a view illustrating an exemplary relationship between thedistance from an attentional pixel and the weighting factor in anotherkernel to be used in the frequency decomposition and differentiated inshape.

FIG. 12D is a view illustrating an exemplary relationship between thedistance from an attentional pixel and the weighting factor in anotherkernel to be used in the frequency decomposition and differentiated inshape.

FIG. 13 is a view schematically illustrating an exemplary flow ofscattered radiation correction processing D that can be executed by thecontroller illustrated in FIG. 2 according to a fourth exemplaryembodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

Hereinafter, one or more embodiments of the present invention will bedescribed with reference to the drawings. However, the scope of theinvention is not limited to the disclosed embodiments.

First Exemplary Embodiment

[Configuration of Radiographic Imaging System 100]

First, a configuration according to the first exemplary embodiment willbe described. FIG. 1 is a view illustrating an example of the entireconfiguration of the radiographic imaging system 100 according to thepresent exemplary embodiment. As illustrated in FIG. 1, the radiographicimaging system 100 includes an image capturing apparatus 1 and a console2 that are connected in such a manner that data can be transmitted andreceived between them.

The image capturing apparatus 1 includes a radiation detector P, animaging platform 11 on which the radiation detector P is attachable, anda radiation generator 12. The imaging platform 11 includes a holder 11 athat holds the radiation detector P.

The radiation detector P is constituted by a semiconductor image sensor,such as flat panel detector (FPD), and is provided so as to face theradiation generator 12 across a subject H. For example, the radiationdetector P includes a glass substrate and a plurality of detectionelements (pixels) arranged in a matrix pattern, at a predeterminedposition on the substrate, to detect radiations (X rays) emitted fromthe radiation generator 12 and penetrating at least the subject Haccording to their intensities and then convert the detected radiationsinto electric signals and accumulate them. Each pixel includes aswitcher such as a thin film transistor (TFT), for example. Theradiation detector P controls the switcher of each pixel based on imagereading conditions input from the console 2 to switch the reading of theelectric signal accumulated in each pixel and acquires image data byreading the electric signal accumulated in each pixel. Then, theradiation detector P outputs the acquired image data to the console 2.

The radiation generator 12 is disposed at a position where it faces theradiation detector P across the subject H, and performs imaging byirradiating the plurality of radiation detectors P attached to theholder 11 a via a patient serving as the subject H with radiations basedon radiation exposure conditions input from the console 2. The radiationexposure conditions input from the console 2 include, for example, tubecurrent value, tube voltage value, radiation exposure time, mAs value,and SID (indicating the shortest distance between the radiation detectorP and a bulb of the radiation generator 12).

The console 2 outputs imaging conditions, such as radiation exposureconditions and image reading conditions, to the image capturingapparatus 1 to control a radiation imaging operation and a radiographicimage reading operation to be performed by the image capturing apparatus1, and also functions as a radiographic image processing apparatus thatperforms image processing on a radiographic image acquired by the imagecapturing apparatus 1.

As illustrated in FIG. 2, the console 2 includes a controller 21, astorage device 22, an operating device 23, a display device 24, and acommunication device 25, which are mutually connected via a bus 26.

The controller 21 includes a central processing unit (CPU), a randomaccess memory (RAM) and the like. The CPU of the controller 21 reads outsystem programs and various processing programs stored in the storagedevice 22 according to an operation of the operating device 23 anddevelops them in the RAM, and then centrally controls operations to beperformed by respective devices constituting the console 2 as well asthe radiation exposure operation and the reading operation to beperformed by the image capturing apparatus 1 according to the developedprograms. Further, the CPU executes image processing, such as scatteredradiation correction processing A described below, on a radiographicimage transmitted from the radiation detector P of the image capturingapparatus 1.

The storage device 22 is constituted by a nonvolatile semiconductormemory, a hard disk, or the like. The storage device 22 stores variousprograms to be executed by the controller 21, parameters required inexecuting each processing by program, and data representing processingresults. The various programs are stored in the form of readable programcodes, and the controller 21 sequentially executes operations accordingto the program codes.

In addition, the storage device 22 stores imaging conditions (e.g.,radiation exposure conditions and image reading conditions)corresponding to an imaging region. Further, the storage device 22stores imaging order information transmitted from a radiologyinformation system (RIS) or the like, which is not illustrated. Theimaging order information includes patient information, examinationinformation (e.g., examination ID, imaging region (including imagingdirection, such as front, side, A→P, P→A, and the like), and examinationdate).

In addition, the storage device 22 stores a formula (Expression 1)expressing a relationship between pixel value and subject thickness foreach imaging condition. Further, the storage device 22 stores a formula(Expression 2) expressing a relationship between subject thickness andscattered radiation content rate for each imaging region.

The operating device 23 is constituted by a keyboard, including cursorkeys, numerical input keys, and various functional keys, and a pointingdevice such as a mouse, and outputs a key operation on the keyboard oran instruction signal input by a mouse operation to the controller 21.Further, the operating device 23 may include a touch panel on a displayscreen of the display device 24. In this case, the operating device 23outputs an instruction signal input via the touch panel to thecontroller 21. Further, the operating device 23 is equipped with anexposure switch for instructing dynamic imaging to the radiationgenerator 12.

The display device 24 is constituted by a monitor, such as a liquidcrystal display (LCD) or a cathode ray tube (CRT), and displays an inputinstruction from the operating device 23, data, or the like, accordingto an instruction of a display signal input from the controller 21.

The communication device 25 has an interface that performs transmissionand reception of data with each of the radiation generator 12 and theradiation detector P. The communications between the console 2 and theradiation generator 12 or the radiation detector P can be wiredcommunications or wireless communications.

Further, the communication device 25 includes a LAN adapter, a modem, aterminal adapter (TA) and the like, and controls transmission andreception of data with the RIS (not illustrated) or the like connectedto a communication network.

[Operations of Radiographic Imaging System 100]

In a state where the radiation detector P is set in the holder 11 a ofthe image capturing apparatus 1, if imaging order information of animaging target is selected by the operating device 23 in the console 2,imaging conditions (radiation exposure conditions and radiographic imagereading conditions) according to the selected imaging order informationare read out from the storage device 22 and transmitted to the imagecapturing apparatus 1. After the positioning of the subject H iscompleted in the image capturing apparatus 1, if the exposure switch ispressed, the radiation generator 12 emits radiations and the radiationdetector P reads image data of a radiographic image. The read image data(i.e., radiographic image) is transmitted to the console 2.

In the console 2, when the communication device 25 receives theradiographic image from the radiation detector P, the controller 21executes scattered radiation correction processing A. FIG. 3 is aflowchart illustrating an exemplary flow of the scattered radiationcorrection processing A. The scattered radiation correction processing Acan be executed by cooperation between the controller 21 and theprograms stored in the storage device 22.

First, the controller 21 acquires the radiographic image transmittedfrom the radiation detector P via the communication device 25 (step S1).

Next, the controller 21 performs edge determination processing on theradiographic image (step S2).

In the edge determination processing, first, the controller 21designates each pixel of the radiographic image as an attentional pixeland sets a region of m pixels×n pixels (m and n are positive integers)including the attentional pixel positioned at the center thereof as anedge determination region. The edge determination region is the same asa convolution region (R in FIG. 4) in filter processing to be performedin a subsequent stage. Next, in each edge determination region, thecontroller 21 calculates a difference between a pixel value of theattentional pixel and a pixel value of each pixel (that is referred toas “referential pixel”) in the edge determination region. In this case,the controller 21 can determine that the edge is stronger as thedifference between the pixel value of the attentional pixel and thepixel value of the referential pixel is larger. Therefore, in thepresent exemplary embodiment, the difference between the pixel value ofthe attentional pixel and the pixel value of the referential pixel isused as a determination result of the edge intensity at the referentialpixel. Instead of the difference between the pixel value of theattentional pixel and the pixel value of the referential pixel, a ratio(for example, a ratio having a numerator being the larger one, in thisembodiment) may be used.

Next, the controller 21 sets a weighting factor to be used in theconvolution calculation during the filter processing based on the edgedetermination result (step S3).

In step S3, the controller 21 sets the weighting factor for eachreferential pixel of each edge determination region. As illustrated inFIG. 5, the setting of the weighting factor is performed in such amanner that the weighting factor becomes larger as the difference (orratio) in pixel value between the attentional pixel and the referentialpixel is smaller (when the edge is weak or there is no edge) and theweighting factor becomes smaller as the difference (or ratio) in pixelvalue between the attentional pixel and the referential pixel is larger(when the edge is strong). The relationship between the difference (orratio) in pixel value between the attentional pixel and the referentialpixel and the weighting factor can be optimally obtained throughexperiments and stored beforehand in the storage device 22.

Alternatively, in step S2, the controller 21 can obtain a variance valueof the pixel value in the edge determination region and may determinethat the edge around the attentional pixel is strong as the variancevalue is large and also determine that the edge around the attentionalpixel is weak as the variance value is small. Further, weighting factors(for example, refer to FIG. 12A to FIG. 12D) differentiated according tothe distance between the attentional pixel and the referential pixel canbe stored beforehand in the storage device 22. In step S3, thecontroller 21 can set the weighting factor by adjusting the weightingfactor stored beforehand in such a manner that the weight becomessmaller as the edge becomes larger (as the variance value becomeslarger) and the weight becomes larger as the edge becomes smaller (asthe variance value becomes smaller).

Next, the controller 21 performs filter processing on the radiographicimage using the weighting factor having been set to generate a frequencycomponent image (step S4).

In the filter processing, as illustrated in FIG. 4, the controller 21designates each pixel of the radiographic image as an attentional pixeland sets a region of m pixels×n pixels (m and n are positive integers)including the attentional pixel positioned at the center thereof as afilter region (i.e., a convolution region, indicated by R in FIG. 4).Then, the controller 21 multiplies the pixel value of each pixel in thefilter region by an element of the corresponding position in a templateof filter factors stored beforehand in the storage device 22 and in atemplate of the weighting factors set in step S3 and calculates a sumthereof, and then generates the frequency component image by designatingthe calculated sum as the pixel value of the attentional pixel. Thefilter factor can be, for example, constant for all elements in thefilter region.

Further, the filter factor can be a coefficient (for example, refer toFIG. 12A to FIG. 12D) differentiated according to the distance betweenthe attentional pixel and the referential pixel, and the controller 21can multiply the pixel value of each pixel in the filter region by anelement of the corresponding position in the template of the weightingfactors having been set based on an edge determination result determinedusing the template of the filter factors and the difference or ratiobetween the pixel value of the attentional pixel and the pixel value ofthe referential pixel and calculate a sum thereof. Then, the controller21 can generate the frequency component image by performing bilateralfilter processing using the calculated sum as the pixel value of theattentional pixel.

In the filter processing, since the frequency band of a filter processedimage is determined by the kernel (i.e., the coefficient to bemultiplied with the pixel value in the filter region), performing thefilter processing using the kernel obtained by multiplying the filterfactor by the weighting factor based on the edge determination resultcan change the frequency band to be extracted by the location in theradiographic image (the intensity of the edge at the location). As theweighting factor becomes larger, the frequency component of lowfrequency can be extracted. As the weighting factor becomes smaller, thefrequency component of high frequency can be extracted.

Next, the controller 21 acquires imaging conditions of the radiographicimage and imaging region information as external parameters (step S5),and estimates the subject thickness from the radiographic image based onthe acquired imaging conditions (step S6), and further estimates ascattered radiation content rate from the radiographic image based onthe acquired imaging region and the estimated subject thickness (stepS7).

The controller 21 acquires the imaging region from the imaging orderinformation used for the imaging and acquires imaging conditionscorresponding to the imaging region from the storage device 22. In thepresent exemplary embodiment, acquired as the imaging conditions aretube voltage, mAs value, and SID. In the present exemplary embodiment,the imaging region and the imaging conditions are acquired based on theimaging order information. However, a user may manually input them fromthe operating device 23. The imaging conditions may be acquired from theimage capturing apparatus 1. Further, the processing in steps S5 to S7may be executed concurrently with the processing in steps S2 to S4 ormay be executed earlier.

The subject thickness of each pixel of the radiographic image can beestimated using the following formula (Expression 1).Subject thickness=coefficient A×log(pixel value)+coefficientB  (Expression 1)Here, the coefficients A and B are coefficients determined by theimaging conditions (i.e., tube voltage, mAs value, and SID). Theabove-mentioned formula (Expression 1) is stored in the storage device22 for each imaging condition.

The method for estimating the subject thickness is not limited to theone described above and a conventionally known method (for example,refer to JP 2016-202219A) may be used.

Further, the scattered radiation content rate of each pixel of theradiographic image can be estimated using the following formula(Expression 2).Scattered radiation content rate=coefficient C×log(subjectthickness+coefficient D)+coefficient E  (Expression 2)Here, coefficients C, D, and E are coefficients determined by theimaging region. The above-mentioned formula (Expression 2) is stored inthe storage device 22 for each imaging region.

Further, the following formula (Expression 3) may be stored inassociation with the imaging conditions and the imaging regionbeforehand, and the scattered radiation content rate may be directlyobtained from the pixel value using the formula (Expression 3)corresponding to the imaging conditions and the imaging region.Scattered radiation content rate=coefficient C×log(coefficientA×log(pixel value)+coefficient B+coefficient D)+coefficientE  (Expression 3)

Next, the controller 21 acquires a scattered radiation removal rate asan external parameter (step S8). For example, a user may input thescattered radiation removal rate from the operating device 23. Further,a value in the range from 0 to 100% entered from the operating device 23may be acquired as the scattered radiation removal rate. A tableindicating a relationship between grid ratio and scattered radiationremoval rate may be stored in the storage device 22, and a scatteredradiation removal rate corresponding to a grid ratio entered from theoperating device 23 may be acquired.

Next, the controller 21 estimates a scattered radiation component bymultiplying the scattered radiation content rate for each pixel of thefrequency component image generated in step S4 and generates a scatteredradiation image representing the scattered radiation amount to beremoved from the radiographic image by multiplying the scatteredradiation component by the scattered radiation removal rate (step S9).

Then, the controller 21 subtracts the scattered radiation image from theradiographic image (subtracts the pixel value of the corresponding pixelof the scattered radiation image from the pixel value of each pixel ofthe radiographic image) to generate a radiographic image from which thescattered radiation has been removed (step S10), and then terminates thescattered radiation correction processing A.

FIG. 6A is a view illustrating a result of the scattered radiationremoval based on a frequency component image obtained by performingfilter processing on a radiographic image using a constant weightingfactor. FIG. 6B is a view illustrating a result of the scatteredradiation removal based on a frequency component image obtained byperforming filter processing on a radiographic image using a weightingfactor reflecting the edge intensity (in which the weighting factorbecomes smaller as the edge becomes stronger). As illustrated in FIG.6A, when the weighting factor is constant irrespective of the edgeintensity, the accuracy in estimating the scattered radiation becomesworse as the edge is stronger. Therefore, reproduction errors ofhigh-frequency components in the vicinity of edges occur in theradiographic image from which the scattered radiation has been removed.On the other hand, as illustrated in FIG. 6B, performing the filterprocessing while setting the weighting factor of the kernel to be usedin the filter processing to become smaller as the edge becomes strongercan improve the accuracy in estimating high-frequency components of thescattered radiation for the portion where the edge is strong and canaccurately remove the scattered radiation.

Second Exemplary Embodiment

Next, a second exemplary embodiment of the present invention will bedescribed.

Since the second exemplary embodiment is similar to the first exemplaryembodiment in its configuration and imaging operation, theirdescriptions will be cited. Hereinafter, operations that can beperformed by the console 2 according to the second exemplary embodimentwill be described.

In the console 2, when receiving image data from the radiation detectorP, the controller 21 executes scattered radiation correction processingB. FIG. 7 is a flowchart illustrating an exemplary flow of the scatteredradiation correction processing B. The scattered radiation correctionprocessing B can be executed by cooperation between the controller 21and the programs stored in the storage device 22.

First, the controller 21 acquires a radiographic image transmitted fromthe radiation detector P via the communication device 25 (step S21).

Next, the controller 21 performs non-local means (NLM) filter processingon the radiographic image to generate a frequency component image (stepS22).

The non-local means filter is a filter that performs smoothing whilepreserving edges by using a calculation result of the degree ofsimilarity of a local image as a weighting factor at the time of theconvolution calculation.

The non-local means filter processing will be described below withreference to FIG. 8. The following (1) to (6) is processing to beexecuted while designating each pixel of the radiographic image as anattentional pixel G1, in the non-local means filter processing.

(1) The controller 21 sets a region of m pixels×n pixels (m and n arepositive integers) including the attentional pixel G1 positioned at thecenter thereof as an attentional region.

(2) The controller 21 sets a filter region around the attentional region(including the attentional region).

(3) The controller 21 designates each pixel in the filter region as areferential pixel G2, and sets a region of m pixels×n pixels (m and nare positive integers) including the referential pixel G2 positioned atthe center thereof as a referential region.

(4) The controller 21 calculates the degree of similarity between theattentional region and the referential region. For example, the squaresum of the difference between the pixel value of each pixel in theattentional region and the pixel value of the corresponding position inthe referential region can be calculated as the degree of similaritybetween the attentional region and the referential region, although itis not limited specifically. In this case, the controller 21 candetermine that the edge is stronger as the degree of similarity betweenthe attentional region and the referential region is lower. Therefore,in the present exemplary embodiment, the calculated degree of similaritycan be used as a determination result of the edge intensity.(5) The controller 21 calculates a weighted average of respective pixelsin the filter region while designating the calculated degree ofsimilarity as a weighting factor of the referential pixel G2.(6) The controller 21 replaces the value of the attentional pixel G1with the calculated weighted average. By executing the processing of (1)to (6) for all pixels, the controller 21 generates the frequencycomponent image.

In the filter processing, since the frequency band of a filter processedimage is determined by the kernel, performing the filter processingusing a weighting factor based on the edge determination result as thekernel can change the frequency band to be extracted by the location inthe radiographic image (the intensity of the edge at the location).

Next, the controller 21 acquires imaging conditions of the radiographicimage and imaging region information as external parameters (step S23),and estimates the subject thickness from the radiographic image based onthe acquired imaging conditions (step S24), and further estimates ascattered radiation content rate from the radiographic image based onthe acquired imaging region and the estimated subject thickness (stepS25). The processing in steps S23 to S25 may be executed concurrentlywith the processing in step S22 or may be executed earlier.

Next, the controller 21 acquires a scattered radiation removal rate asan external parameter (step S26).

Next, the controller 21 multiplies each pixel in the frequency componentimage generated in step S22 by the scattered radiation content rate toestimate a scattered radiation component and multiplies the scatteredradiation component by the scattered radiation removal rate to generatea scattered radiation image representing the scattered radiation amountto be removed from the radiographic image (step S27).

Then, the controller 21 subtracts the scattered radiation image from theradiographic image to generate a radiographic image from which thescattered radiation has been removed (step S28), and terminates thescattered radiation correction processing B.

In the second exemplary embodiment, similar to the first exemplaryembodiment, by performing the filter processing on the radiographicimage with the weighting factor becoming smaller as the edge becomesstronger (as the degree of similarity becomes smaller), the accuracy inestimating high-frequency components of the scattered radiation can beimproved for strong edge portions, and the scattered radiation can beaccurately removed.

Third Exemplary Embodiment

Next, a third exemplary embodiment of the present invention will bedescribed.

Since the third exemplary embodiment is similar to the first exemplaryembodiment in its configuration and imaging operation, theirdescriptions will be cited. Hereinafter, operations that can beperformed by the console 2 according to the third exemplary embodimentwill be described.

In the console 2, when receiving image data from the radiation detectorP, the controller 21 executes scattered radiation correction processingC. FIG. 9 is a flowchart illustrating an exemplary flow of the scatteredradiation correction processing C. The scattered radiation correctionprocessing C can be executed by cooperation between the controller 21and the programs stored in the storage device 22.

First, the controller 21 acquires a radiographic image transmitted fromthe radiation detector P via the communication device 25 (step S31).

Next, the controller 21 performs edge determination processing on theradiographic image (step S32).

The edge determination processing in step S32 is, for example, the edgedetermination processing (including the one using the variance value)described in step S2 in FIG. 3 or the edge determination processingusing the degree of similarity calculated through the processing of (1)to (4) described in step S22 of FIG. 7, or the like.

Next, the controller 21 sets a weighting factor to be used in theconvolution calculation during the filter processing based on the edgedetermination result (step S33).

In step S33, the controller 21 sets the weighting factor for thereferential pixel in each edge determination region. In the presentembodiment, the setting of the weighting factor is performed in such amanner that the weighting factor becomes smaller as the edge is weakeror when there is no edge (as the difference or ratio in pixel valuebetween the attentional pixel and the referential pixel calculated inthe edge determination processing is smaller, the variance value issmaller, or the degree of similarity is larger) and becomes larger asthe edge is stronger (as the difference or ratio in pixel value betweenthe attentional pixel and the referential pixel calculated in edgedetermination processing is larger, the variance value is larger, or thedegree of similarity is smaller). In the storage device 22, thedifference in pixel value between the attentional pixel and thereferential pixel (or the ratio, the variance value or the degree ofsimilarity) is stored beforehand in relation to the weighting factor.

Next, the controller 21 performs frequency decomposition on theradiographic image using the weighting factor having been set andgenerates frequency component images of a plurality of frequency bands(a plurality of frequency band images) (step S34).

For example, one of the following (A) and (B) is employable as themethod of frequency decomposition.

(A) Using a kernel being constant in size and shape to generatefrequency component image of a plurality of frequency bands.

(B) Using kernels differentiated in size and/or shape to generatefrequency component image of a plurality of frequency bands.

According to above-mentioned method (A), for example, as illustrated inFIG. 10, the controller 21 first generates an unsharp image 1 byperforming filter processing (e.g., a simple averaging filter, abinominal filter, a Gaussian filter, or the like) on an inputradiographic image (an original image) using a kernel K1 being constantin size and shape, which is prepared beforehand (stored in the storagedevice 22). Then, the controller 21 performs filter processing on theunsharp image 1 using the kernel K1 to generate an unsharp image 2.Next, the controller 21 performs filter processing on the unsharp image2 using the kernel K1 to generate an unsharp image 3. Then, thecontroller 21 generates a high-frequency component image by obtaining adifference between the original image and the unsharp image 1, amedium-frequency component image by obtaining a difference between theunsharp image 1 and the unsharp image 2, and a low-frequency componentimage by obtaining a difference between the unsharp image 2 and theunsharp image 3.

Namely, in step S34, the controller 21 generates a plurality of unsharpimages by performing filter processing using a kernel obtained bymultiplying the kernel K1 having been set beforehand by the weightingfactor set in step S33, and generates a plurality of frequency bandimages (e.g., high-frequency component image, medium-frequency componentimage, and low-frequency component image) using the plurality ofgenerated unsharp images.

According to above-mentioned method (B), for example, as illustrated inFIG. 11, the controller 21 performs filter processing (for example, thesimple averaging filter, the binominal filter, the Gaussian filter, orthe like) on an original image using kernels K2 to K4 differentiated insize and/or shape to generate a plurality of unsharp images 1 to 3different in frequency band. Then, the controller 21 generates ahigh-frequency component image by obtaining a difference between theoriginal image and the unsharp image 1, a medium-frequency componentimage by obtaining a difference between the unsharp image 1 and theunsharp image 2, and a low-frequency component image by obtaining adifference between the unsharp image 2 and the unsharp image 3.

Namely, in step S34, the controller 21 generates a plurality of unsharpimages by performing filter processing using kernels obtained bymultiplying the kernels K2 to K4 having been set beforehand by theweighting factor set in step S33, and generates frequency componentimages of a plurality of frequency bands (e.g., high-frequency componentimage, medium-frequency component image, and low-frequency componentimage) using the generated plurality of unsharp images.

In the description of (A) and (B) using FIG. 10 and FIG. 11, althoughthree unsharp images are generated to generate frequency componentimages of three frequency bands (high-frequency component image,medium-frequency component image, and low-frequency component image),this is only an example. Frequency component images of a plurality ofnecessary bands can be generated by generating a plurality of unsharpimages and obtaining their differences.

When the filter processing is performed using kernels different in size,it is feasible to extract different frequency components according tothe size of each kernel. The larger the kernel size is, the higher theeffect of smoothing is. This is useful in extracting low-frequencycomponents. The smaller the kernel size is, the lower the effect ofsmoothing is. This is useful in extracting high-frequency components.More specifically, when the kernels K2 to K4 are differentiated in size,the size of kernel K2<the size of kernel K3<the size of kernel K4.

Further, when the filter processing is performed using kernels differentin shape, it is feasible to extract different frequency componentsaccording to the shape of each kernel. The kernels different in shapeare, for example, kernels different in weighting factor to be multipliedwith the filter factor having been set beforehand according to thedistance between the attentional pixel and the referential pixel. FIG.12A to FIG. 12D illustrate examples of the weighting factor. Asillustrated in FIG. 12A, when using a kernel whose weighting factorchanges steeply as the distance from the attentional pixel is shorter,the effect of smoothing is lower and accordingly high-frequencycomponents can be extracted. As illustrated in FIG. 12D, when using akernel whose weighting factor changes gradually according to thedistance from the attentional pixel, the effect of smoothing is higherand accordingly low-frequency components can be extracted.

The frequency bands of the frequency components to be extracted in stepS34 and the kernels to be used in extracting the frequency componentimages are set (stored in the storage device 22) beforehand based onexperiments.

Next, the controller 21 acquires imaging conditions of the radiographicimage and imaging region information as external parameters (step S35),and estimates the subject thickness from the radiographic image based onthe acquired imaging conditions (step S36), and further estimates ascattered radiation content rate from the radiographic image based onthe acquired imaging region and the estimated subject thickness (stepS37). The processing in steps S35 to S37 may be executed concurrentlywith the processing in steps S32 to S34 or may be executed earlier.

Next, the controller 21 multiplies each pixel of the frequency componentimage of each frequency band generated in step S34 by the scatteredradiation content rate to generate a scattered radiation component imageestimating the scattered radiation component of each frequency band, andthen combines them (step S38).

Next, the controller 21 acquires a scattered radiation removal rate asan external parameter (step S39), and multiplies the combined scatteredradiation component image by the scattered radiation removal rate togenerate a scattered radiation image indicating the scattered radiationamount to be removed (step S40).

Then, the controller 21 subtracts the scattered radiation image from theradiographic image to generate a radiographic image from which thescattered radiation has been removed (step S41), and terminates thescattered radiation correction processing C.

In the third exemplary embodiment, the radiographic image is designatedas the original image, the filter processing is repetitively performedusing the kernel whose weighting factor becomes larger as the edge isstronger to generate unsharp images of a plurality of frequency bands,and the generated unsharp images are subtracted from the original imageto generate frequency band images of the plurality of frequency bands.Accordingly, it is feasible to extract high-frequency components of thescattered radiation for strong edge portions. The accuracy in estimatinghigh-frequency components of the scattered radiation can be improved forstrong edge portions, and the scattered radiation can be accuratelyremoved. Further, compared to the first and second exemplaryembodiments, the third exemplary embodiment brings an effect that it iseasy to extract the scattered radiation of an aimed frequency component.

Fourth Exemplary Embodiment

Next, a fourth exemplary embodiment of the present invention will bedescribed.

Since the fourth exemplary embodiment is similar to the first exemplaryembodiment in its configuration and imaging operation, theirdescriptions will be cited. Hereinafter, operations that can beperformed by the console 2 according to the fourth exemplary embodimentwill be described.

In the console 2, when receiving image data from the radiation detectorP, the controller 21 executes scattered radiation correction processingD. FIG. 13 is a flowchart illustrating an exemplary flow of thescattered radiation correction processing D. The scattered radiationcorrection processing D can be executed by cooperation between thecontroller 21 and the programs stored in the storage device 22.

First, the controller 21 acquires a radiographic image transmitted fromthe radiation detector P via the communication device 25 (step S51).

Next, the controller 21 performs edge determination processing on theradiographic image (step S52).

In step S52, first, the controller 21 designates each pixel of theradiographic image as an attentional pixel, and sets a region of mpixels×n pixels (m and n are positive integers) including theattentional pixel positioned at the center thereof as an edgedetermination region. Next, in each edge determination region, thecontroller 21 calculates a variance value of the pixel value in theregion and determines the edge intensity based on the variance value.For example, the controller 21 determines that the edge is stronger asthe variance value is larger and the edge is weaker as the variancevalue is smaller. Alternatively, the controller 21 may obtain adifference or ratio between an average of respective pixel values in theedge determination region and the pixel value of the attentional pixel,and may determine that the edge is stranger as the difference or ratiois larger and weaker as the difference or ratio is smaller.

Next, the controller 21 sets a weighting factor to be used for afrequency component image of each frequency band to be generated in stepS54, for each pixel, based on the edge determination result (step S53).For example, the setting of the weighting factor is performed in such amanner that the weighting factor applied to the frequency componentimage of the high-frequency band becomes larger as the peripheral edgeof the pixel is stronger and the weighting factor applied to thefrequency component image of the low-frequency band becomes smaller asthe peripheral edge of the pixel is weaker. The relationship between theedge intensity (variance value) and the weighting factor applied to thefrequency component image of each frequency band is determined based onexperiments and stored beforehand in the storage device 22.

Next, the controller 21 performs frequency decomposition on theradiographic image and generates frequency component images of aplurality of frequency bands (step S54).

In step S54, for example, the controller 21 performs the frequencydecomposition according to the method (A) or (B) described in step S34of the scattered radiation correction processing C according to thethird exemplary embodiment. In this step S54, the controller 21 does notuse the weighting factor set in step S53.

Next, the controller 21 multiplies each of the generated frequencycomponent images of the plurality of frequency bands by the weightingfactor set in step S53 to generate a plurality of weighted frequencycomponent images (step S55).

Next, the controller 21 acquires imaging conditions of the radiographicimage and imaging region information as external parameters (step S56),and estimates the subject thickness from the radiographic image based onthe acquired imaging conditions (step S57), and further estimates ascattered radiation content rate from the radiographic image based onthe acquired imaging region and the estimated subject thickness (stepS58). The processing in steps S56 to S58 may be executed concurrentlywith the processing in steps S52 to S55 or may be executed earlier.

Next, the controller 21 multiplies each pixel of the frequency componentimage of each frequency band, to which the weighting factor has beenmultiplied in step S55, by the scattered radiation content rate togenerate a scattered radiation component image estimating the scatteredradiation component of each frequency band, and then combines them (stepS59).

Next, the controller 21 acquires a scattered radiation removal rate asan external parameter (step S60), multiplies the combined scatteredradiation component image by the scattered radiation removal rate togenerate a scattered radiation image indicating the scattered radiationamount to be removed (step S61).

Then, the controller 21 subtracts the scattered radiation image from theradiographic image to generate a radiographic image from which thescattered radiation has been removed (step S62), and terminates thescattered radiation correction processing D.

In the fourth exemplary embodiment, the weight of the high-frequencyband image included in the scattered radiation image to be used inestimating the scattered radiation becomes stranger as the edge in theregion is stronger. Therefore, the accuracy in estimating high-frequencycomponents of the scattered radiation can be improved for strong edgeportions, and the scattered radiation can be accurately removed.Further, compared to the first and second exemplary embodiments, thefourth exemplary embodiment brings an effect that it is easy to extractthe scattered radiation of an aimed frequency component.

As mentioned above, the controller 21 of the console 2 determines theintensity of an edge in a radiographic image obtained byradiographically imaging a subject, sets a weighting factor to be usedin extracting a frequency component of a predetermined frequency bandfrom the radiographic image according to a determination result,extracts the frequency component from the radiographic image using theweighting factor having been set, and multiplies the extracted frequencycomponent by the scattered radiation content rate to estimate thescattered radiation component in radiographic image. Then, thecontroller 21 multiplies the estimated scattered radiation component bythe scattered radiation removal rate to generate the scattered radiationimage representing the scattered radiation component to be removed fromthe radiographic image, and performs scattered radiation correction onthe radiographic image by subtracting the scattered radiation image fromthe radiographic image.

Accordingly, it is feasible to improve the accuracy in estimating thescattered radiation in the vicinity of edges in the radiographic image,and therefore it is feasible to obtain a radiographic image from whichthe scattered radiation has been precisely removed.

The contents described in the above-mentioned exemplary embodiments arepreferred examples, and the present invention is not limited to theseexamples.

For example, in the above-mentioned exemplary embodiments, the presentinvention is applied to a radiographic image of a chest. However, thepresent invention is also applicable to a radiographic image capturinganother region.

Further, in the above-mentioned exemplary embodiments, the console 2controlling the image capturing apparatus 1 is functionally operable asthe radiographic image processing apparatus. However, the radiographicimage processing apparatus may be separated from the console.

Further, for example, in the above-mentioned description, the hard diskand the semiconductor nonvolatile memory are practical examples of acomputer readable medium storing the programs according to the presentinvention. However, the computer readable medium is not limited to theseexamples. For example, a portable storage medium such as a compact diskread only memory (CD-ROM) is employable as a computer readable medium.Further, carrier waves are employable as a medium capable of providingdata of the programs according to the present invention via acommunication line.

Further, detailed configurations and detailed operations of respectivedevices constituting the radiographic imaging system can beappropriately modified without departing from the gist of the presentinvention.

Although embodiments of the present invention have been described andillustrated in detail, the disclosed embodiments are made for purposesof illustration and example only and not limitation. The scope of thepresent invention should be interpreted by terms of the appended claims.

The entire disclosure of Japanese Patent Application No. 2018-009644filed on Jan. 24, 2018 including the specification, claims, drawings,and abstract is incorporated herein by reference in its entirety.

What is claimed is:
 1. A radiographic image processing apparatuscomprising a hardware processor, which determines the intensity of anedge in a radiographic image obtained by radiographically imaging asubject, sets a weighting factor to be used in extracting a frequencycomponent from the radiographic image according to a determinationresult of the edge intensity, extracts the frequency component from theradiographic image using the weighting factor having been set,multiplies the extracted frequency component by a scattered radiationcontent rate to estimate a scattered radiation component in theradiographic image, multiplies the estimated scattered radiationcomponent by a scattered radiation removal rate to generate a scatteredradiation image representing the scattered radiation component to beremoved from the radiographic image, and performs scattered radiationcorrection on the radiographic image by subtracting the scatteredradiation image from the radiographic image.
 2. The radiographic imageprocessing apparatus according to claim 1, wherein the hardwareprocessor sets each pixel of the radiographic image as an attentionalpixel and sets a plurality of pixels around the attentional pixel asreferential pixels, calculates a difference or a ratio in pixel valuebetween each referential pixel and the attentional pixel, and determinesthe intensity of an edge around the attentional pixel based on themagnitude of the calculated difference or ratio.
 3. The radiographicimage processing apparatus according to claim 1, wherein the hardwareprocessor sets each pixel of the radiographic image as an attentionalpixel and sets a region of a plurality of peripheral pixels includingthe attentional pixel positioned at the center thereof as an attentionalregion, and determines the intensity of an edge around the attentionalpixel based on a calculation result of the degree of similarity betweenthe attentional region and a peripheral referential region.
 4. Theradiographic image processing apparatus according to claim 1, whereinthe hardware processor sets each pixel of the radiographic image as anattentional pixel and sets an edge determination region including aplurality of pixels and the attentional pixel positioned at the centerthereof, and determines the intensity of an edge around the attentionalpixel based on a variance value of a pixel value in the edgedetermination region.
 5. The radiographic image processing apparatusaccording to claim 1, wherein the hardware processor sets a largerweighting factor as the edge having been determined is weaker and sets asmaller weighting factor as the edge having been determined is stronger,and extracts the frequency component from the radiographic image byperforming filter processing on the radiographic image using a kernelgenerated by using the weighting factor having been set.
 6. Theradiographic image processing apparatus according to claim 1, whereinthe hardware processor sets a smaller weighting factor as the edgehaving been determined is weaker and sets a large weighting factor asthe edge having been determined is stronger, and extracts frequencycomponents of a plurality of frequency bands by performing frequencydecomposition on the radiographic image using a kernel generated byusing the weighting factor having been set.
 7. The radiographic imageprocessing apparatus according to claim 1, wherein the hardwareprocessor sets the weighting factor for each frequency band in such away as to set a larger weighting factor applied to a frequency componentof a high-frequency band as the edge having been determined is strongerand set a larger weighting factor applied to a frequency component of alow-frequency band as the edge having been determined is weaker,extracts frequency components of a plurality of frequency bands byperforming frequency decomposition on the radiographic image using akernel prepared beforehand and being constant in size and shape or aplurality of kernels prepared beforehand and differentiated in sizeand/or shape, and multiplies each of the extracted frequency componentsof the plurality of frequency bands by the weighting factor having beenset.
 8. A scattered radiation correction method for a radiographic imageprocessing apparatus that performs scattered radiation correction on aradiographic image obtained by radiographically imaging a subject, themethod comprising: determining the intensity of an edge in theradiographic image; setting a weighting factor to be used in extractinga frequency component from the radiographic image according to adetermination result of the edge intensity; extracting the frequencycomponent from the radiographic image using the weighting factor havingbeen set; multiplying the extracted frequency component by a scatteredradiation content rate to estimate a scattered radiation component inthe radiographic image; multiplying the estimated scattered radiationcomponent by a scattered radiation removal rate to generate a scatteredradiation image representing the scattered radiation component to beremoved from the radiographic image; and performs scattered radiationcorrection on the radiographic image by subtracting the scatteredradiation image from the radiographic image.
 9. A non-transitorycomputer readable storage medium storing a program that causes acomputer, to be used for a radiographic image processing apparatus thatperforms scattered radiation correction on a radiographic image obtainedby radiographically imaging a subject, to determine the intensity of anedge in the radiographic image obtained by radiographically imaging thesubject, set a weighting factor to be used in extracting a frequencycomponent from the radiographic image according to a determinationresult of the edge intensity, extract the frequency component from theradiographic image using the weighting factor having been set, multiplythe extracted frequency component by a scattered radiation content rateto estimate a scattered radiation component in the radiographic image,multiply the estimated scattered radiation component by a scatteredradiation removal rate to generate a scattered radiation imagerepresenting the scattered radiation component to be removed from theradiographic image, and perform scattered radiation correction on theradiographic image by subtracting the scattered radiation image from theradiographic image.